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We present a sample cTWAS report based on real data analysis. The analyzed trait is prostate cancer, the prediction models are Prostate & Testis & Lymphocytes gene expression and splicing models trained on GTEx v8 in the PredictDB format.

Analysis Settings

Input Data

  • GWAS Z-scores

The summary statistics for prostate cancer are downloaded from https://www.ebi.ac.uk/gwas/downloads/summary-statistics, using dataset ID: GCST90274714.

The sample size is

[1] "gwas_n = 726828"
  • Prediction models

The prediction models used in this analysis are prostate & testis & lymphocytes gene expression and splicing models, trained on GTEx v8 in the PredictDB format. These models can be downloaded from https://predictdb.org/post/2021/07/21/gtex-v8-models-on-eqtl-and-sqtl/

  • Reference data

We did not include LD reference in the analysis.

Data processing and harmonization

We map the reference SNPs to regions following the instructions from the cTWAS tutorial.

When processing z-scores, we exclude multi-allelic and strand-ambiguous variants by setting drop_multiallelic = TRUE and drop_strand_ambig = TRUE.

The process can be divided into steps below, users can expand the code snippets below to view the exact code used.

  • Input and output settings
weight_prostate_expression_file <- system.file("extdata/project_data", 
                                               "mashr_Prostate_e.db", package = "ctwas")
weight_prostate_splicing_file <- system.file("extdata/project_data", 
                                             "mashr_Prostate_s.db", package = "ctwas")
weight_testis_expression_file <- system.file("extdata/project_data", 
                                             "mashr_Testis_e.db", package = "ctwas")
weight_testis_splicing_file <- system.file("extdata/project_data", 
                                           "mashr_Testis_s.db", package = "ctwas")
weight_lymphocytes_expression_file <- system.file("extdata/project_data", 
                                                  "mashr_Cells_EBV-transformed_lymphocytes_e.db", package = "ctwas")
weight_lymphocytes_splicing_file <- system.file("extdata/project_data", 
                                                "mashr_Cells_EBV-transformed_lymphocytes_s.db", package = "ctwas")

z_snp <- vroom::vroom("~/Desktop/Prostate Cancer Project/GCST90274714.mod.tsv.gz", col_names = TRUE, show_col_types = FALSE)
z_snp$Z <- z_snp$beta / z_snp$standard_error

z_snp <- z_snp[, c("rsid", "other_allele", "effect_allele", "Z")]
colnames(z_snp) <- c("id", "A1", "A2", "z")

region_file <- system.file("extdata/ldetect", "EUR.b38.ldetect.regions.RDS", package = "ctwas")
region_info <- readRDS(region_file)

## other parameters
ncore <- 6
  • Preprocessing GWAS
### Preprocess SNP_map
ref_snp_info_file <- system.file("extdata/project_data", "ukb_b38_0.1_var_info.Rvar.gz", package = "ctwas")

ref_snp_info <- data.table::fread(ref_snp_info_file, sep = "\t")
class(ref_snp_info) <- "data.frame"

res <- create_snp_map(region_info, ref_snp_info)
region_info <- res$region_info
snp_map <- res$snp_map

### Preprocess GWAS z-scores
z_snp <- preprocess_z_snp(z_snp, snp_map, 
                          drop_multiallelic = TRUE, 
                          drop_strand_ambig = TRUE)
  • Preprocessing weights
weights_prostate_expression <- preprocess_weights(weight_prostate_expression_file,
                                                  region_info,
                                                  gwas_snp_ids = z_snp$id,
                                                  snp_map = snp_map,
                                                  type = "expression",
                                                  context = "prostate",
                                                  weight_name = "prostate_expression",
                                                  weight_format = "PredictDB",
                                                  drop_strand_ambig = TRUE,
                                                  scale_predictdb_weights = TRUE,
                                                  load_predictdb_LD = TRUE,
                                                  filter_protein_coding_genes = TRUE,
                                                  ncore = 6)
weights_prostate_splicing <- preprocess_weights(weight_prostate_splicing_file,
                                                region_info,
                                                gwas_snp_ids = z_snp$id,
                                                snp_map = snp_map,
                                                type = "splicing",
                                                context = "prostate",
                                                weight_name = "prostate_splicing",
                                                weight_format = "PredictDB",
                                                drop_strand_ambig = TRUE,
                                                scale_predictdb_weights = TRUE,
                                                load_predictdb_LD = TRUE,
                                                filter_protein_coding_genes = TRUE,
                                                ncore = 6)

weights_testis_expression <- preprocess_weights(weight_testis_expression_file,
                                                region_info,
                                                gwas_snp_ids = z_snp$id,
                                                snp_map = snp_map,
                                                type = "expression",
                                                context = "testis",
                                                weight_name = "testis_expression",
                                                weight_format = "PredictDB",
                                                drop_strand_ambig = TRUE,
                                                scale_predictdb_weights = TRUE,
                                                load_predictdb_LD = TRUE,
                                                filter_protein_coding_genes = TRUE,
                                                ncore = 6)
weights_testis_splicing <- preprocess_weights(weight_testis_splicing_file,
                                              region_info,
                                              gwas_snp_ids = z_snp$id,
                                              snp_map = snp_map,
                                              type = "splicing",
                                              context = "testis",
                                              weight_name = "testis_splicing",
                                              weight_format = "PredictDB",
                                              drop_strand_ambig = TRUE,
                                              scale_predictdb_weights = TRUE,
                                              load_predictdb_LD = TRUE,
                                              filter_protein_coding_genes = TRUE,
                                              ncore = 6)

weights_lymphocytes_expression <- preprocess_weights(weight_lymphocytes_expression_file,
                                                     region_info,
                                                     gwas_snp_ids = z_snp$id,
                                                     snp_map = snp_map,
                                                     type = "expression",
                                                     context = "lymphocytes",
                                                     weight_name = "lymphocytes_expression",
                                                     weight_format = "PredictDB",
                                                     drop_strand_ambig = TRUE,
                                                     scale_predictdb_weights = TRUE,
                                                     load_predictdb_LD = TRUE,
                                                     filter_protein_coding_genes = TRUE,
                                                     ncore = 6)
weights_lymphocytes_splicing <- preprocess_weights(weight_lymphocytes_splicing_file,
                                                   region_info,
                                                   gwas_snp_ids = z_snp$id,
                                                   snp_map = snp_map,
                                                   type = "splicing",
                                                   context = "lymphocytes",
                                                   weight_name = "lymphocytes_splicing",
                                                   weight_format = "PredictDB",
                                                   drop_strand_ambig = TRUE,
                                                   scale_predictdb_weights = TRUE,
                                                   load_predictdb_LD = TRUE,
                                                   filter_protein_coding_genes = TRUE,
                                                   ncore = 6)

weights <- c(
  weights_prostate_expression,
  weights_prostate_splicing,
  weights_testis_expression,
  weights_testis_splicing,
  weights_lymphocytes_expression,
  weights_lymphocytes_splicing)

Running cTWAS analysis

We use the ctwas main function ctwas_sumstats_noLD to run the cTWAS analysis without LD. For more details on this function, refer to the cTWAS tutorial: https://xinhe-lab.github.io/multigroup_ctwas/articles/minimal_tutorial.html

All arguments are set to their default values.

Users can expand the code snippets below to view the exact code used.

ctwas_res <- ctwas_sumstats_noLD(z_snp,
                                 weights,
                                 region_info,
                                 snp_map,
                                 thin = 0.1, 
                                 ncore = 6)

Parameter estimation

ctwas_res is the object contains the outputs of cTWAS

We extract the estimated parameters by param <- ctwas_res$param

We make plots using the function make_convergence_plots(param, gwas_n) to see how estimated parameters converge during the execution of the program:

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These plots show the estimated prior inclusion probability, prior effect size variance, enrichment and proportion of variance explained (PVE) over the iterations of parameter estimation. The enrichment is defined as the ratio of the prior inclusion probability of molecular traits over the prior inclusion probability of variants. We generally expect molecular traits to have higher prior inclusion probability than variants. Enrichment values typically range from 20 - 100 for expression traits.

Then, we use summarize_param(param, gwas_n) to obtain estimated parameters (from the last iteration) and to compute the PVE by variants and molecular traits.

[1] "The number of genes/introns/SNPs used in the analysis is:"
   prostate|expression      prostate|splicing      testis|expression 
                  9693                  29875                  11361 
       testis|splicing lymphocytes|expression   lymphocytes|splicing 
                 50036                   8478                  26609 
                   SNP 
               7146350 

ctwas_parameters$prop_heritability contains the proportion of heritability mediated by molecular traits and variants, we visualize it using pie chart.

ctwas_parameters <- summarize_param(param, gwas_n)
data <- data.frame(
  category = names(ctwas_parameters$prop_heritability),
  percentage = ctwas_parameters$prop_heritability
)
# Calculate percentage labels for the chart
data$percentage_label <- paste0(round(data$percentage * 100, 1), "%")

ggplot(data, aes(x = "", y = percentage, fill = category)) +
  geom_bar(stat = "identity", width = 1) +
  coord_polar("y", start = 0) +
  theme_void() +  # Remove background and axes
  geom_text(aes(label = percentage_label), 
            position = position_stack(vjust = 0.5)) +
  scale_fill_brewer(palette = "Pastel1") +
  labs(fill = "Category") +
  ggtitle("Percent of heritability")

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Diagnosis plots

For all genes analyzed, we compare the z-scores and fine-mapping PIPs”

ggplot(data = finemap_res[finemap_res$type!="SNP",], aes(x = abs(z), y = susie_pip)) +
  geom_point() +
  labs(x = "abs(z-scores)", y = "PIPs") +
  theme_minimal()

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Fine-mapping results

We process the fine-mapping results here.

We first add gene annotations to cTWAS results.

mapping_table is the combination of both expression and splicing data.

finemap_res <- anno_finemap_res(finemap_res,
                                snp_map = snp_map,
                                mapping_table = mapping_table,
                                add_gene_annot = TRUE,
                                map_by = "molecular_id",
                                drop_unmapped = TRUE,
                                add_position = TRUE,
                                use_gene_pos = "mid")

The annotated fine-mapping results, ones within credible sets are shown

finemap_res_show <- finemap_res[!is.na(finemap_res$cs) &finemap_res$type !="SNP",]

DT::datatable(finemap_res_show,caption = htmltools::tags$caption( style = 'caption-side: topleft; text-align = left; color:black;','The annotated fine-mapping results, ones within credible sets are shown'),options = list(pageLength = 5) )
Warning in instance$preRenderHook(instance): It seems your data is too big for
client-side DataTables. You may consider server-side processing:
https://rstudio.github.io/DT/server.html

Next, we compute gene PIPs across different types of molecular traits.

library(dplyr)

susie_alpha_res <- ctwas_res$susie_alpha_res

susie_alpha_res <- anno_susie_alpha_res(susie_alpha_res,
                                        mapping_table = mapping_table,
                                        map_by = "molecular_id",
                                        drop_unmapped = TRUE)

Gene PIPs, only genes within credible sets are shown

library(dplyr)
susie_alpha_res <- anno_susie_alpha_res(susie_alpha_res,
                                        mapping_table = mapping_table,
                                        map_by = "molecular_id",
                                        drop_unmapped = TRUE)
combined_pip_by_group <- combine_gene_pips(susie_alpha_res,
                                          group_by = "gene_name",
                                          by = "group",
                                          method = "combine_cs",
                                          filter_cs = TRUE,
                                          include_cs_id = TRUE)
combined_pip_table <- subset(combined_pip_by_group, combined_pip > 0.8)
DT::datatable(combined_pip_table)

GSEA Analysis

Welcome to enrichR
Checking connection ... 
Enrichr ... Connection is Live!
FlyEnrichr ... Connection is Live!
WormEnrichr ... Connection is Live!
YeastEnrichr ... Connection is Live!
FishEnrichr ... Connection is Live!
OxEnrichr ... Connection is Live!
[1] "The number of genes used in enrichment analysis = 38"
Uploading data to Enrichr... Done.
  Querying GO_Biological_Process_2021... Done.
  Querying GO_Cellular_Component_2021... Done.
  Querying GO_Molecular_Function_2021... Done.
Parsing results... Done.
[1] "GO_Biological_Process_2021"

[1] "GO_Cellular_Component_2021"

[1] "GO_Molecular_Function_2021"
Warning in plotEnrich(GO_enrichment[[db]]): There are duplicated trimmed names
in the plot, consider increasing the 'numChar' setting.

Locus plots (from highest PIP to lowest 0.8 cutoff)

make_locusplot(finemap_res,
               region_id = "20_34225635_36332043",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:04:42.157176 INFO::Limit to protein coding genes
2024-10-15 21:04:42.161285 INFO::focal id: ENSG00000126001.15|testis_expression
2024-10-15 21:04:42.16501 INFO::focal molecular trait: CEP250 testis expression
2024-10-15 21:04:42.165292 INFO::Range of locus: chr20:34225783-36331600
chromosome 20, position 34225783 to 36331600
4318 SNPs/datapoints
2024-10-15 21:04:42.429671 INFO::focal molecular trait QTL positions: 35445740,35454222,35456125
2024-10-15 21:04:42.445005 INFO::Limit PIPs to credible sets
Warning: ggrepel: 880 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

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make_locusplot(finemap_res,
               region_id = "2_240620667_241210506",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:04:43.809488 INFO::Limit to protein coding genes
2024-10-15 21:04:43.810049 INFO::focal id: intron_2_241195845_241199316|prostate_splicing
2024-10-15 21:04:43.810274 INFO::focal molecular trait: ANO7 prostate splicing
2024-10-15 21:04:43.810528 INFO::Range of locus: chr2:240618245-241608572
chromosome 2, position 240618245 to 241608572
2174 SNPs/datapoints
2024-10-15 21:04:43.956085 INFO::focal molecular trait QTL positions: 241195850,241202304
2024-10-15 21:04:43.968902 INFO::Limit PIPs to credible sets
Warning: ggrepel: 213 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

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make_locusplot(finemap_res,
               region_id = "19_54099074_55216712",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:04:44.808958 INFO::Limit to protein coding genes
2024-10-15 21:04:44.80958 INFO::focal id: ENSG00000170892.10|testis_expression
2024-10-15 21:04:44.809835 INFO::focal molecular trait: TSEN34 testis expression
2024-10-15 21:04:44.810107 INFO::Range of locus: chr19:54098580-55244488
chromosome 19, position 54098580 to 55244488
4136 SNPs/datapoints
2024-10-15 21:04:44.927332 INFO::focal molecular trait QTL positions: 54189591,54190017
2024-10-15 21:04:44.940202 INFO::Limit PIPs to credible sets
Warning: ggrepel: 388 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

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make_locusplot(finemap_res,
               region_id = "17_150263_1269105",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:04:46.026885 INFO::Limit to protein coding genes
2024-10-15 21:04:46.027509 INFO::focal id: ENSG00000179409.10|prostate_expression
2024-10-15 21:04:46.027763 INFO::focal molecular trait: GEMIN4 prostate expression
2024-10-15 21:04:46.028037 INFO::Range of locus: chr17:150409-1727661
chromosome 17, position 150409 to 1727661
4317 SNPs/datapoints
2024-10-15 21:04:46.108767 INFO::focal molecular trait QTL positions: 715725
2024-10-15 21:04:46.121726 INFO::Limit PIPs to credible sets
Warning: ggrepel: 210 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

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make_locusplot(finemap_res,
               region_id = "11_124625632_126441425",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:04:46.918789 INFO::Limit to protein coding genes
2024-10-15 21:04:46.919451 INFO::focal id: ENSG00000165495.15|prostate_expression
2024-10-15 21:04:46.919714 INFO::focal molecular trait: PKNOX2 prostate expression
2024-10-15 21:04:46.919997 INFO::Range of locus: chr11:124627414-126441118
chromosome 11, position 124627414 to 126441118
5527 SNPs/datapoints
2024-10-15 21:04:47.005055 INFO::focal molecular trait QTL positions: 125184897
2024-10-15 21:04:47.017848 INFO::Limit PIPs to credible sets
Warning: ggrepel: 542 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

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make_locusplot(finemap_res,
               region_id = "16_84412277_85115079",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:04:47.988604 INFO::Limit to protein coding genes
2024-10-15 21:04:47.989195 INFO::focal id: ENSG00000153786.12|prostate_expression
2024-10-15 21:04:47.989437 INFO::focal molecular trait: ZDHHC7 prostate expression
2024-10-15 21:04:47.989704 INFO::Range of locus: chr16:84412178-85114834
chromosome 16, position 84412178 to 85114834
3456 SNPs/datapoints
2024-10-15 21:04:48.225914 INFO::focal molecular trait QTL positions: 85011497,85011520,85018213
2024-10-15 21:04:48.238923 INFO::Limit PIPs to credible sets
Warning: ggrepel: 155 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

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make_locusplot(finemap_res,
               region_id = "2_236540389_237852338",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:04:48.979434 INFO::Limit to protein coding genes
2024-10-15 21:04:48.980045 INFO::focal id: ENSG00000115648.13|lymphocytes_expression
2024-10-15 21:04:48.980303 INFO::focal molecular trait: MLPH lymphocytes expression
2024-10-15 21:04:48.980578 INFO::Range of locus: chr2:236541810-237851575
chromosome 2, position 236541810 to 237851575
4211 SNPs/datapoints
2024-10-15 21:04:49.041691 INFO::focal molecular trait QTL positions: 237484645,237484791
2024-10-15 21:04:49.054701 INFO::Limit PIPs to credible sets
Warning: ggrepel: 130 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

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make_locusplot(finemap_res,
               region_id = "1_153208353_154797927",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:04:49.757071 INFO::Limit to protein coding genes
2024-10-15 21:04:49.757692 INFO::focal id: ENSG00000143545.8|lymphocytes_expression
2024-10-15 21:04:49.757935 INFO::focal molecular trait: RAB13 lymphocytes expression
2024-10-15 21:04:49.758198 INFO::Range of locus: chr1:153208786-154797763
chromosome 1, position 153208786 to 154797763
3641 SNPs/datapoints
2024-10-15 21:04:49.842692 INFO::focal molecular trait QTL positions: 153985724,153989308
2024-10-15 21:04:49.855553 INFO::Limit PIPs to credible sets
Warning: ggrepel: 432 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Version Author Date
314c305 yy896 2024-10-07
93f8704 yy896 2024-10-07
fce136d yy896 2024-10-04
make_locusplot(finemap_res,
               region_id = "19_46646825_48778970",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:04:50.849321 INFO::Limit to protein coding genes
2024-10-15 21:04:50.85002 INFO::focal id: ENSG00000105327.17|prostate_expression
2024-10-15 21:04:50.850308 INFO::focal molecular trait: BBC3 prostate expression
2024-10-15 21:04:50.850602 INFO::Range of locus: chr19:46646725-48778681
chromosome 19, position 46646725 to 48778681
6583 SNPs/datapoints
2024-10-15 21:04:50.932913 INFO::focal molecular trait QTL positions: 47232618
2024-10-15 21:04:50.945721 INFO::Limit PIPs to credible sets
Warning: ggrepel: 738 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Version Author Date
314c305 yy896 2024-10-07
93f8704 yy896 2024-10-07
fce136d yy896 2024-10-04
make_locusplot(finemap_res,
               region_id = "1_203365606_204711940",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:04:52.561131 INFO::Limit to protein coding genes
2024-10-15 21:04:52.561752 INFO::focal id: ENSG00000133056.13|lymphocytes_expression
2024-10-15 21:04:52.562039 INFO::focal molecular trait: PIK3C2B lymphocytes expression
2024-10-15 21:04:52.562327 INFO::Range of locus: chr1:203365611-204711982
chromosome 1, position 203365611 to 204711982
3607 SNPs/datapoints
2024-10-15 21:04:52.626081 INFO::focal molecular trait QTL positions: 204495053
2024-10-15 21:04:52.640659 INFO::Limit PIPs to credible sets
Warning: ggrepel: 137 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Version Author Date
314c305 yy896 2024-10-07
93f8704 yy896 2024-10-07
fce136d yy896 2024-10-04
make_locusplot(finemap_res,
               region_id = "22_17813322_19924835",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:04:53.40685 INFO::Limit to protein coding genes
2024-10-15 21:04:53.407541 INFO::focal id: ENSG00000184058.12|prostate_expression
2024-10-15 21:04:53.407832 INFO::focal molecular trait: TBX1 prostate expression
2024-10-15 21:04:53.408125 INFO::Range of locus: chr22:17813372-19925414
chromosome 22, position 17813372 to 19925414
4739 SNPs/datapoints
2024-10-15 21:04:53.666853 INFO::focal molecular trait QTL positions: 19762002
2024-10-15 21:04:53.680158 INFO::Limit PIPs to credible sets
Warning: ggrepel: 262 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Version Author Date
314c305 yy896 2024-10-07
93f8704 yy896 2024-10-07
fce136d yy896 2024-10-04
make_locusplot(finemap_res,
               region_id = "20_33027017_34225635",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:04:54.606309 INFO::Limit to protein coding genes
2024-10-15 21:04:54.606862 INFO::focal id: ENSG00000101417.11|lymphocytes_expression
2024-10-15 21:04:54.607085 INFO::focal molecular trait: PXMP4 lymphocytes expression
2024-10-15 21:04:54.607337 INFO::Range of locus: chr20:33027532-34224952
chromosome 20, position 33027532 to 34224952
1953 SNPs/datapoints
2024-10-15 21:04:54.660451 INFO::focal molecular trait QTL positions: 33720469
2024-10-15 21:04:54.673576 INFO::Limit PIPs to credible sets
Warning: ggrepel: 123 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Version Author Date
314c305 yy896 2024-10-07
93f8704 yy896 2024-10-07
fce136d yy896 2024-10-04
make_locusplot(finemap_res,
               region_id = "2_205870980_207780675",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:04:55.417541 INFO::Limit to protein coding genes
2024-10-15 21:04:55.418162 INFO::focal id: intron_2_207165706_207166757|lymphocytes_splicing
2024-10-15 21:04:55.418419 INFO::focal molecular trait: MIR7845 lymphocytes splicing
2024-10-15 21:04:55.418698 INFO::Range of locus: chr2:205871698-207779797
chromosome 2, position 205871698 to 207779797
4879 SNPs/datapoints
2024-10-15 21:04:55.481664 INFO::focal molecular trait QTL positions: 207166747
2024-10-15 21:04:55.49484 INFO::Limit PIPs to credible sets
Warning: ggrepel: 199 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Version Author Date
314c305 yy896 2024-10-07
93f8704 yy896 2024-10-07
fce136d yy896 2024-10-04
make_locusplot(finemap_res,
               region_id = "10_101189482_102620653",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:04:56.274087 INFO::Limit to protein coding genes
2024-10-15 21:04:56.274666 INFO::focal id: ENSG00000138111.14|prostate_expression
2024-10-15 21:04:56.274919 INFO::focal molecular trait: MFSD13A prostate expression
2024-10-15 21:04:56.275183 INFO::Range of locus: chr10:101190250-102621720
chromosome 10, position 101190250 to 102621720
2735 SNPs/datapoints
2024-10-15 21:04:56.334827 INFO::focal molecular trait QTL positions: 102462097,102463206,102466080
2024-10-15 21:04:56.348246 INFO::Limit PIPs to credible sets
Warning: ggrepel: 412 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Version Author Date
314c305 yy896 2024-10-07
93f8704 yy896 2024-10-07
fce136d yy896 2024-10-04
make_locusplot(finemap_res,
               region_id = "8_81044160_81781504",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:04:57.427966 INFO::Limit to protein coding genes
2024-10-15 21:04:57.428506 INFO::focal id: ENSG00000164695.4|prostate_expression
2024-10-15 21:04:57.428728 INFO::focal molecular trait: CHMP4C prostate expression
2024-10-15 21:04:57.428978 INFO::Range of locus: chr8:81039839-81781010
chromosome 8, position 81039839 to 81781010
1855 SNPs/datapoints
2024-10-15 21:04:57.481856 INFO::focal molecular trait QTL positions: 81741409
2024-10-15 21:04:57.494828 INFO::Limit PIPs to credible sets
Warning: ggrepel: 64 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Version Author Date
314c305 yy896 2024-10-07
93f8704 yy896 2024-10-07
fce136d yy896 2024-10-04
make_locusplot(finemap_res,
               region_id = "1_37083582_38266175",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:04:58.215795 INFO::Limit to protein coding genes
2024-10-15 21:04:58.21637 INFO::focal id: ENSG00000163874.10|prostate_expression
2024-10-15 21:04:58.216614 INFO::focal molecular trait: ZC3H12A prostate expression
2024-10-15 21:04:58.216873 INFO::Range of locus: chr1:37083938-38266050
chromosome 1, position 37083938 to 38266050
3063 SNPs/datapoints
2024-10-15 21:04:58.276059 INFO::focal molecular trait QTL positions: 37475037,37499397
2024-10-15 21:04:58.289056 INFO::Limit PIPs to credible sets
Warning: ggrepel: 227 unlabeled data points (too many overlaps). Consider
increasing max.overlaps
Warning: ggrepel: 46 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Version Author Date
314c305 yy896 2024-10-07
93f8704 yy896 2024-10-07
fce136d yy896 2024-10-04
make_locusplot(finemap_res,
               region_id = "12_11601912_12580594",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:04:59.14063 INFO::Limit to protein coding genes
2024-10-15 21:04:59.141181 INFO::focal id: ENSG00000121380.12|prostate_expression
2024-10-15 21:04:59.141427 INFO::focal molecular trait: BCL2L14 prostate expression
2024-10-15 21:04:59.141691 INFO::Range of locus: chr12:11034257-12580271
chromosome 12, position 11034257 to 12580271
2897 SNPs/datapoints
2024-10-15 21:04:59.199662 INFO::focal molecular trait QTL positions: 12052195,12052348
2024-10-15 21:04:59.213108 INFO::Limit PIPs to credible sets
Warning: ggrepel: 62 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Version Author Date
314c305 yy896 2024-10-07
93f8704 yy896 2024-10-07
fce136d yy896 2024-10-04
make_locusplot(finemap_res,
               region_id = "12_106564970_108632125",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:04:59.879106 INFO::Limit to protein coding genes
2024-10-15 21:04:59.879716 INFO::focal id: ENSG00000120832.9|testis_expression
2024-10-15 21:04:59.879993 INFO::focal molecular trait: MTERF2 testis expression
2024-10-15 21:04:59.880283 INFO::Range of locus: chr12:106564986-108631756
chromosome 12, position 106564986 to 108631756
5509 SNPs/datapoints
2024-10-15 21:04:59.941092 INFO::focal molecular trait QTL positions: 106988381
2024-10-15 21:04:59.954807 INFO::Limit PIPs to credible sets
Warning: ggrepel: 212 unlabeled data points (too many overlaps). Consider
increasing max.overlaps
Warning: ggrepel: 13 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Version Author Date
314c305 yy896 2024-10-07
93f8704 yy896 2024-10-07
fce136d yy896 2024-10-04
make_locusplot(finemap_res,
               region_id = "4_38905401_40200989",
               ens_db = ens_db,
               weights = weights,
               highlight_pip = 0.8,
               filter_protein_coding_genes = TRUE,
               filter_cs = TRUE,
               color_pval_by = "cs",
               color_pip_by = "cs")
2024-10-15 21:05:01.011138 INFO::Limit to protein coding genes
2024-10-15 21:05:01.011761 INFO::focal id: ENSG00000121897.14|prostate_expression
2024-10-15 21:05:01.012024 INFO::focal molecular trait: LIAS prostate expression
2024-10-15 21:05:01.012287 INFO::Range of locus: chr4:38905595-40200074
chromosome 4, position 38905595 to 40200074
3803 SNPs/datapoints
2024-10-15 21:05:01.070003 INFO::focal molecular trait QTL positions: 39465159
2024-10-15 21:05:01.083008 INFO::Limit PIPs to credible sets
Warning: ggrepel: 256 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Version Author Date
314c305 yy896 2024-10-07
93f8704 yy896 2024-10-07
fce136d yy896 2024-10-04

sessionInfo()
R version 4.4.1 (2024-06-14)
Platform: aarch64-apple-darwin20
Running under: macOS 15.0.1

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRblas.0.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.0

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: America/New_York
tzcode source: internal

attached base packages:
[1] stats4    stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
 [1] enrichR_3.2               data.table_1.16.2        
 [3] lubridate_1.9.3           forcats_1.0.0            
 [5] stringr_1.5.1             dplyr_1.1.4              
 [7] purrr_1.0.2               tidyr_1.3.1              
 [9] tibble_3.2.1              tidyverse_2.0.0          
[11] ggrepel_0.9.6             ggplot2_3.5.1            
[13] EnsDb.Hsapiens.v86_2.99.0 ensembldb_2.28.1         
[15] AnnotationFilter_1.28.0   GenomicFeatures_1.56.0   
[17] AnnotationDbi_1.66.0      Biobase_2.64.0           
[19] GenomicRanges_1.56.1      GenomeInfoDb_1.40.1      
[21] IRanges_2.38.1            S4Vectors_0.42.1         
[23] BiocGenerics_0.50.0       ctwas_0.4.16             
[25] readr_2.1.5               workflowr_1.7.1          

loaded via a namespace (and not attached):
  [1] RColorBrewer_1.1-3          rstudioapi_0.16.0          
  [3] jsonlite_1.8.9              magrittr_2.0.3             
  [5] farver_2.1.2                rmarkdown_2.28             
  [7] fs_1.6.4                    BiocIO_1.14.0              
  [9] zlibbioc_1.50.0             vctrs_0.6.5                
 [11] memoise_2.0.1               Rsamtools_2.20.0           
 [13] RCurl_1.98-1.16             mixsqp_0.3-54              
 [15] htmltools_0.5.8.1           S4Arrays_1.4.1             
 [17] curl_5.2.3                  SparseArray_1.4.8          
 [19] sass_0.4.9                  bslib_0.8.0                
 [21] htmlwidgets_1.6.4           plotly_4.10.4              
 [23] zoo_1.8-12                  cachem_1.1.0               
 [25] gggrid_0.2-0                GenomicAlignments_1.40.0   
 [27] whisker_0.4.1               lifecycle_1.0.4            
 [29] pkgconfig_2.0.3             Matrix_1.7-0               
 [31] R6_2.5.1                    fastmap_1.2.0              
 [33] GenomeInfoDbData_1.2.12     MatrixGenerics_1.16.0      
 [35] digest_0.6.37               colorspace_2.1-1           
 [37] ps_1.8.0                    rprojroot_2.0.4            
 [39] irlba_2.3.5.1               crosstalk_1.2.1            
 [41] RSQLite_2.3.7               WriteXLS_6.7.0             
 [43] labeling_0.4.3              pgenlibr_0.3.7             
 [45] timechange_0.3.0            fansi_1.0.6                
 [47] httr_1.4.7                  abind_1.4-8                
 [49] compiler_4.4.1              bit64_4.5.2                
 [51] withr_3.0.1                 BiocParallel_1.38.0        
 [53] DBI_1.2.3                   highr_0.11                 
 [55] DelayedArray_0.30.1         rjson_0.2.23               
 [57] tools_4.4.1                 httpuv_1.6.15              
 [59] glue_1.8.0                  restfulr_0.0.15            
 [61] callr_3.7.6                 promises_1.3.0             
 [63] grid_4.4.1                  getPass_0.2-4              
 [65] generics_0.1.3              LDlinkR_1.4.0              
 [67] gtable_0.3.5                tzdb_0.4.0                 
 [69] locuszoomr_0.3.5            hms_1.1.3                  
 [71] utf8_1.2.4                  XVector_0.44.0             
 [73] pillar_1.9.0                later_1.3.2                
 [75] logging_0.10-108            lattice_0.22-6             
 [77] rtracklayer_1.64.0          bit_4.5.0                  
 [79] tidyselect_1.2.1            Biostrings_2.72.1          
 [81] knitr_1.48                  git2r_0.33.0.9000          
 [83] ProtGenerics_1.36.0         SummarizedExperiment_1.34.0
 [85] xfun_0.48                   matrixStats_1.4.1          
 [87] DT_0.33                     stringi_1.8.4              
 [89] UCSC.utils_1.0.0            lazyeval_0.2.2             
 [91] yaml_2.3.10                 evaluate_1.0.1             
 [93] codetools_0.2-20            cli_3.6.3                  
 [95] munsell_0.5.1               processx_3.8.4             
 [97] jquerylib_0.1.4             Rcpp_1.0.13                
 [99] png_0.1-8                   XML_3.99-0.17              
[101] parallel_4.4.1              blob_1.2.4                 
[103] bitops_1.0-9                viridisLite_0.4.2          
[105] scales_1.3.0                crayon_1.5.3               
[107] rlang_1.1.4                 cowplot_1.1.3              
[109] KEGGREST_1.44.1